btergm: Temporal Exponential Random Graph Models by Bootstrapped Pseudolikelihood

Temporal Exponential Random Graph Models (TERGM) estimated by maximum pseudolikelihood with bootstrapped confidence intervals or Markov Chain Monte Carlo maximum likelihood. Goodness of fit assessment for ERGMs, TERGMs, and SAOMs. Micro-level interpretation of ERGMs and TERGMs. The methods are described in Leifeld, Cranmer and Desmarais (2018), JStatSoft <doi:10.18637/jss.v083.i06>.

Package details

AuthorPhilip Leifeld [aut, cre], Skyler J. Cranmer [ctb], Bruce A. Desmarais [ctb]
MaintainerPhilip Leifeld <philip.leifeld@essex.ac.uk>
LicenseGPL (>= 2)
Version1.10.11
URL https://github.com/leifeld/btergm
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("btergm")

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btergm documentation built on Oct. 6, 2023, 1:07 a.m.